metadata
license: apache-2.0
base_model: Langboat/mengzi-bert-base-fin
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: >-
mengzi-bert-base-fin-finetuning-wallstreetcn-morning-news-market-overview-open-000001SH-v1
results: []
mengzi-bert-base-fin-finetuning-wallstreetcn-morning-news-market-overview-open-000001SH-v1
This model is a fine-tuned version of Langboat/mengzi-bert-base-fin on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2948
- Accuracy: 0.7241
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 38 | 0.6799 | 0.5517 |
| No log | 2.0 | 76 | 0.6132 | 0.7241 |
| No log | 3.0 | 114 | 0.6453 | 0.6207 |
| No log | 4.0 | 152 | 0.7017 | 0.7586 |
| No log | 5.0 | 190 | 0.9160 | 0.7241 |
| No log | 6.0 | 228 | 1.0803 | 0.7586 |
| No log | 7.0 | 266 | 1.1766 | 0.7241 |
| No log | 8.0 | 304 | 1.1976 | 0.7586 |
| No log | 9.0 | 342 | 1.2610 | 0.7241 |
| No log | 10.0 | 380 | 1.2948 | 0.7241 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.2
- Tokenizers 0.13.3